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Bastiat’s Bastions

What is seen and what is unseen.


Archive for September, 2009

The Seasons Change, and So Do I

Friday, September 11th, 2009

With most school districts in the country having resumed operations by this last week, someone asked me about the effect of people going back to school on the country’s economy.  Well, this is actually very simple.  Every year when school vacations begin, unemployment goes up and when school starts back up, the nation’s unemployment rate goes back down.  Total employment usually goes up in the summer as well, as many outside jobs open up, especially for teens. 

Definitions are important here, as how we define things affects how we measure them.  The unemployment rate is not how many people do not have jobs, as not everyone is looking for a job.  School children in high school often do not seek jobs in the summer, but even fewer look for jobs during the school year.  Should we count as unemployed those who aren’t even in the market?  The answer is no.  Think of someone calling people up in a survey.  They first ask the person’s age, then whether the person has a job.  Then they ask if the person looked for a job in the past month.  Those who neither have a job nor have looked for a job are counted as not being in the labor force.  The rest, those with jobs or have actively looked for a job in the last month, are counted as being in the labor force.  Of those in the labor force, those who do not have a job, are counted as unemployed.  So, to be counted among the unemployed, a person has to be without a job now and has to have been actively looking for work.

A bureau within the U.S. Department of Labor, the Bureau of Labor Statistics (BLS), surveys a rather large group of households across the country to find out what percent of the labor force is without a job, the unemployment rate.  Below are some historical unemployment figures from the BLS website

Labor Force Statistics from the Current Population Survey

Series Id:           LNU04000000
Not Seasonally Adjusted
Series title:        (Unadj) Unemployment Rate
Labor force status:  Unemployment rate
Type of data:        Percent
Age:                 16 years and over

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

1999

4.8

4.7

4.4

4.1

4.0

4.5

4.5

4.2

4.1

3.8

3.8

3.7

4.2

2000

4.5

4.4

4.3

3.7

3.8

4.1

4.2

4.1

3.8

3.6

3.7

3.7

4.0

2001

4.7

4.6

4.5

4.2

4.1

4.7

4.7

4.9

4.7

5.0

5.3

5.4

4.7

2002

6.3

6.1

6.1

5.7

5.5

6.0

5.9

5.7

5.4

5.3

5.6

5.7

5.8

2003

6.5

6.4

6.2

5.8

5.8

6.5

6.3

6.0

5.8

5.6

5.6

5.4

6.0

2004

6.3

6.0

6.0

5.4

5.3

5.8

5.7

5.4

5.1

5.1

5.2

5.1

5.5

2005

5.7

5.8

5.4

4.9

4.9

5.2

5.2

4.9

4.8

4.6

4.8

4.6

5.1

2006

5.1

5.1

4.8

4.5

4.4

4.8

5.0

4.6

4.4

4.1

4.3

4.3

4.6

2007

5.0

4.9

4.5

4.3

4.3

4.7

4.9

4.6

4.5

4.4

4.5

4.8

4.6

2008

5.4

5.2

5.2

4.8

5.2

5.7

6.0

6.1

6.0

6.1

6.5

7.1

5.8

2009

8.5

8.9

9.0

8.6

9.1

9.7

9.7

9.6

 

 

 

 

 

 A bureau within the U.S. Department of Labor, the Bureau of Labor Statistics (BLS), surveys a rather large group of households across the country to find out what percent of the labor force is without a job, the unemployment rate.  Below are some historical unemployment figures from the BLS website. 

 Note that every June this number seems to go up from the month before and every September the number drops back down by about the same amount.  Every December, the figure drops off and rises in January.  All of these amount to predictable patterns, that economists and statisticians call “seasonality.” 

By the way, here are the unemployment rates for the same time period, but with adjustments made for seasonality.

 Labor Force Statistics from the Current Population Survey 

Series Id:           LNS14000000
Seasonal Adjusted
Series title:        (Seas) Unemployment Rate
Labor force status:  Unemployment rate
Type of data:        Percent
Age:                 16 years and over

Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

1999

4.3

4.4

4.2

4.3

4.2

4.3

4.3

4.2

4.2

4.1

4.1

4.0

 

2000

4.0

4.1

4.0

3.8

4.0

4.0

4.0

4.1

3.9

3.9

3.9

3.9

 

2001

4.2

4.2

4.3

4.4

4.3

4.5

4.6

4.9

5.0

5.3

5.5

5.7

 

2002

5.7

5.7

5.7

5.9

5.8

5.8

5.8

5.7

5.7

5.7

5.9

6.0

 

2003

5.8

5.9

5.9

6.0

6.1

6.3

6.2

6.1

6.1

6.0

5.8

5.7

 

2004

5.7

5.6

5.8

5.6

5.6

5.6

5.5

5.4

5.4

5.5

5.4

5.4

 

2005

5.2

5.4

5.2

5.2

5.1

5.1

5.0

4.9

5.0

5.0

5.0

4.8

 

2006

4.7

4.8

4.7

4.7

4.7

4.6

4.7

4.7

4.5

4.4

4.5

4.4

 

2007

4.6

4.5

4.4

4.5

4.5

4.6

4.7

4.7

4.7

4.8

4.7

4.9

 

2008

4.9

4.8

5.1

5.0

5.5

5.6

5.8

6.2

6.2

6.6

6.8

7.2

 

2009

7.6

8.1

8.5

8.9

9.4

9.5

9.4

9.7

 

 

 

 

 

The rise in summer unemployment is mostly in teenage unemployment as teens enter the labor market looking for summer jobs.  Summer employment actually expands, but so does unemployment as not all of the job seekers find what they are looking for.  With the start of school, this pattern reverses itself.  Not that with increased retail activity in the Christmas shopping season, the same thing happens.  To keep from confusing monthly rises and falls in employment or unemployment rates with more serious changes beyond these mere seasonal patterns, economists and statisticians adjust the raw figures by the seasonal pattern.  If December unemployment rates run 0.2 percentage points lower than average and January’s rates run 0.3 percentage points, then these months’ rates are adjusted by 0.2 upward in December and 0.3 percentage points downward in January.

Not only do statisticians make adjustments of this sort, but so do retailers and so do families.  For instance, my job is a nine-month position, and I get paid in those nine months.  I stash money aside the months I work so that I can maintain a similar spending pattern every month.  I can predict it, so I do not get caught by surprise.

 So, when you read about monthly changes in employment and unemployment figures or even gasoline pump prices, before being alarmed, check to see if the figures you are viewing are seasonally adjusted or not.   While our trees in the deep south may not change that much, our economic seasons change much the way the rest of the country changes.

 -MC

Lob STER WARS

Friday, September 11th, 2009

Lob STER WARS

On a small island off of the coast of Maine, lobstermen are shooting at each other (Lobster wars rock remote Maine island, Clarke Canfield, Associated Press Writer).  Much like urban gangbangers, they are fighting over profitable territory.  And just like their urban counterparts, the territory under dispute is “un-ownable” or for the lobstermen, un-ownable under current state laws.  But, just as with the gangbangers, they are enforcing their property rights themselves.  With both street territory and fishing territory, agreement as to ownership or property rights reduces conflict and violence. 

When property rights are under dispute, conflicts arise.  When property rights are not enforced by a more powerful authority, such as the state, these conflicts are not settled in courts with lawyers and judges, but in the streets or the seas with AK-47s or 12-guage shotguns.  This is especially costly in human lives.  It also causes people to invest in weapons and armor and shooting skills rather than in boats and fishing skills. 

The violence in the Maine lobster fisheries is nothing new.  J.M. Acheson (Capturing the Commons: Devising Institutions to Manage the Maine Lobster Fishery, 2003) discusses how gangs of Maine lobster fishermen restrict access to what they consider their territory by cutting lobster trap lines, so that they cannot be retrieved.  Ahceson notes that in areas where gangs defend their territory, the lobsters were bigger and more pounds of lobsters were caught per trap.

Property rights are the rules of the game, telling us who gets to make what decisions in what circumstances.  Different property rights result in different outcomes.  Certain property rights regimes allow who ever gets there first to rule.  For instance, open access fisheries where the fish are considered private property only after being caught, can have disastrous results.  Think for a moment about a population of fish where anyone can take whatever fish they can catch.  As long as the fish can be sold for more than it costs to catch the fish, a profit is available to fishermen, more people become fishermen, prices of fish drop and costs to fishing rise.  As more people turn to fishing and total fishing effort intensifies, the population of fish drops.  This continues until the prices drop far enough and the costs to the fishermen rise enough, that it is no longer more profitable than other ventures for these fishermen and the number of fishermen levels off. 

There is just one problem with all of this.  The fishermen, as individuals, do not bear all of the costs of their actions.  There are two distinct cost categories that we should recognize. 

One of these costs is the cost of catching or harvesting the fish.  These costs are born completely by the individual fishermen.  This includes not only their fuel, boat, and fishing gear, but also the cost of their time spent fishing.

Another cost of catching or harvesting fish is the cost of reduced populations in the future.  When the future populations of the fish drop, it becomes more costly to catch the same amount of fish.  This cost from increased future scarcity is sometimes called “scarcity costs.”  In the case of open access fisheries, this scarcity cost from of a reduced future population is borne by all of the fishermen, as a group–it is shared, so that each fisherman only faces a small part of their own costs.  This also means that all of them face costs imposed on them by the rest.

What happens when costs are borne individually is that the action is only undertaken when the benefits of the action exceed the costs.  But when someone bears only a portion of the costs of their actions, they do more of that action than they would if they bore the entire costs.   So, when fishermen harvest so much that the fish population decreases, no fisherman connects their fishing activity this year with the falling fish population and the rising difficulty of catching fish next year.  Also, each fisherman recognizes that even if he reduces his fishing this year to make fishing more sustainable, other fishermen will just catch what he did not, nullifying his individual efforts toward sustainability.  Under these circumstances, no fisherman has an incentive to cut back on fishing, and the population of fish dwindles.

While the defense of territory by these lobster gangs increases the incomes of lobstermen and moves lobster fishing toward sustainability, it could be pushed even further toward sustainability and the level of violence and destruction of traps could be brought down if Maine would follow something that we do in Louisiana with oyster production.  Louisiana leases areas to oystermen, establishing state recognized property rights.  While the state cannot always be there to enforce leases rights against encroachment (and theft), the oystermen are backed up by the state.  Anyone caught tampering with oysters on a leased bed face state-enforced penalties.  While oystermen do often have to protect their own property, they clearly have an advantage by being backed up by game wardens, sheriffs, and the courts.  They do not have to point guns as much as they would if they had no recognized claim. 

-MC

Tourist Illusions as a Market Signal

Thursday, September 10th, 2009

If you visit a local McDonald’s for lunch and encounter a long line, you probably view the experience as a sign of poor service.  While on vacation, however, you may not perceive a long line in the same way.  An anecdote to follow suggests that tourists, in the absence of complete information, often flock to the restaurants and other attractions that feature the longest lines.  There are several reasons for this apparent behavior.  Firstly, many tourists lack information and thus view long lines as a signal that informed tourists believe an attraction to represent a good experience.  In this sense, long lines at tourists spots are self-reinforcing and therefore valued by tourist-driven firms as more than an end result of good business practices (i.e., to maintain sales momentum).  Secondly, some tourists value common experience.  A tourist who enjoys discussing common experiences with friends might seek popular spots (long lines) to increase the likelihood of such conversations.  Lastly, tourists aren’t typically pressed for time and are therefore more willing to trade time for an experience that is likely to be memorable. 

An examination of firm behavior allows us to attribute these motivations and behaviors to the average tourist.  Specifically, several tourist-driven firms are observed to create the illusion that clients are pouring out the door of their establishment.  However, the author has observed no examples of this queuing illusion among firms that are not tourist-driven.  The cases surrounding this observation center upon Café du Monde, a popular New Orleans tourist spot.  The author has never visited Café du Monde due to its almost ever-present, amusement park sized line.  The author has, on the other hand, visited several nearby cafes.  A few such cafes, including Café Beignet, depend upon the business of residual tourists who came to Café du Monde but could not wait the necessary time for service there.  There is no doubt that Café Beignet enjoys a steady stream of business.  However, the café exaggerates its own popularity by preventing each waiting customer from approaching the register until it is his turn to order.  Consequently, the line at Café Beignet begins much closer to the establishment’s door than to its counter and pours onto the outdoor sidewalk even when business is relatively slow.  Some approaching tourists see this and likely think the following: “Café du Monde must be really good given the line, but it will take over an hour to be served there.  Café Beignet must be pretty good given the line, and it will take only fifteen minutes to be served there.  I’ll try Café Beignet.”  Thus, long lines (or the illusion of long lines) beget longer lines at Café Beignet and other nearby cafes that feature the same policy.  Otherwise, why would these already crowded establishments create twenty feet of dead space between the counter and the line of waiting patrons.    

Such a strategy would never work for a firm that hosts a large proportion of repeat customers, as people don’t often fall for the same trick twice.  However, it is a good strategy for Café Beignet, as the typical tourist (a) doesn’t realize the illusion until it is nearly time to order and (b) probably will not be back at any rate.  When on vacation, a tourist should understand that he is not in Kansas anymore.  Firms certainly do. 

-SS